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intelligence (AI) residency) to advance scientific machine learning for clinical oncology. The project builds a hybrid framework that couples an existing quantitative systems pharmacology (QSP) model of cancer
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scientific conferences and publish models and scientific insights in high-impact journals Who You Are: Ph.D. in Computational Biology, Bioinformatics, Computer Science or Machine Learning related field
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discoveries. Who You Are: Ph.D. with a proven track record of excellence in Computer Science and Machine Learning, with substantial domain experience in biology and genomics. Must have advanced at least one key
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-Coding Genome Edits: Develop innovative machine learning approaches for designing precise non-coding genome edits, focusing on how non-coding alterations influence gene regulation and cellular function